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Looking for MLops Engineer Position in Ann Arbor, MI

2 months ago

Ann Arbor, United States ConfigUSA Full time

Title: MLops Engineer

Location: Ann Arbor, Michigan (Still Hybrid Tuesday to Thursday on site)



Need only Deployment Experience, not required build experience.

Responsibilities:

•Design, implement, and maintain end-to-end machine learning pipelines for model training, validation, and deployment.

•Collaborate with data scientists, software engineers, and DevOps engineers to integrate machine learning models into production systems.

•Develop automation tools and frameworks to streamline the machine learning workflow, including data preprocessing, feature engineering, model training, and evaluation.

•Optimize model performance and scalability by leveraging cloud computing resources and distributed computing techniques.

•Implement monitoring and logging solutions to track model performance, data quality, and system health in production.

•Manage model versioning, experimentation, and reproducibility using version control systems and experiment tracking tools.

•Stay up to date with the latest trends and technologies in machine learning, cloud computing, and software engineering, and incorporate them into the MLOps workflow.

•Provide technical guidance and mentorship to junior team members on best practices for MLOps.

**Qualifications: **

•Bachelor's degree or higher in computer science, engineering, mathematics, or related field.

•Strong programming skills in languages such as Python, Java, or Scala.

•Proven experience as an MLOps Engineer, specifically with Azure ML and related Azure technologies.

•Familiarity with containerization technologies such as Docker and orchestration tools like Kubernetes.

•Proficiency in automation tool s like JIRA, Ansible, Jenkins, Docker compose, Artifactory, etc.

•Knowledge of DevOps practices and tools for continuous integration, continuous deployment (CI/CD), and infrastructure as code (IaC).


Feedback from a client for One of Previous Candidate::

Venkata was overqualified overall and too much in Data Science.

  1. About 5+ experience is what they need.
  2. Not a lead but can take requirements from Business and create technical requirements
  3. Strong communication and listening skills (they will be face to face with business)
  4. Multi-task and work independent as a contributor.
  5. Technically needs Machine Learning as most of their experience
  6. Deploying and Monitoring models
  7. MS Azure, SQL Server background.
  8. Data Bricks a plus.